Orthogonal Wide Area Multilateration (WAM) is being considered as one of the primary backup sources of air traffic surveillance to Automatic Dependent Surveillance-Broadcast (ADS-B) in the National Airspace System (NAS). Radar is currently the primary source of air traffic surveillance, with ADS-B poised to succeed radar in coming years. WAM service could serve as both a transition to full ADS-B service and a cost-saving backup surveillance alternative to radar maintenance and expansion.
One of the challenges associated with WAM is the accuracy of the aircraft's reported altitude. The standard way to estimate the altitude of an aircraft leading up to the advent of GPS is the aneroid altimeter. This device actually does not measure altitude but rather the atmospheric pressure outside the cabin. Since atmospheric pressure decreases as altitude increases, pressure data can be converted to altitude data based on the Standard Atmospheric Model tables or formulas. Although the altimeter designs have changed through the years, their method for changing the offset for mean sea level (MSL) is universal. This feature allows the pilot to apply a static offset to the MSL pressure based on a recent nearby barometric reading. This is called the QNH or “altimeter setting” which is available from most airfields via radio voice communication or other methods.
Avionics may have access to a variety of altitude measurements via the aircraft's data bus (e.g. ARINC), including the raw output from the barometric altimeter (reported altitude), altitude indicated on the altimeter dial (indicated altitude), and height above ellipsoid (HAE) which is generated by an onboard GPS system. Aircraft transponders typically include reported altitude in their downlink message transmissions. Examples include Mode C (resolution 100′) for air-traffic control radar beacon system (ATCRBS), DF4 (resolution 25′ or 100′) for Mode S, and the ADS-B Airborne Position Message/State Vector Element (resolution 25′ or 100′) for ADS-B. In the case of ADS-B, GPS derived height above ellipsoid (HAE) may be reported as well in the messages transmitted.
There are several reasons why application of the Standard Atmospheric Model fails to yield an accurate reported altitude from pressure measurements. First, surface atmospheric pressure is not constant and varies with the area and time. Second, surface temperature is not constant. Since air density decreases with temperature, moving from a warm area to a colder one leads to the real altitude being lower than the indicated one. Third, air composition is not constant. The most varying component is water vapor: humidity influences the pressure lapse rate. Thus, flights in the pre-GPS times (or in the uncertain GPS reception conditions, like those in the mountainous regions) required rather frequent adjustments of altimeter settings based on the guidance from Air Traffic Control (ATC). Even this could not guarantee the accuracy of the altitude data since atmospheric conditions for pilots served by the same ATC are different.
Multilateration (MLAT) systems provide a reasonably cost-effective surveillance solution in areas where conventional radar would be ineffective, such as in mountainous regions. A typical MLAT system includes four or more spatially distributed ground receivers, each of which is networked to a central processor. The receivers are positioned so that when aircraft under surveillance transmit ADS-B squitters or replies to ATCRBS or Mode S interrogations, the RF message is received at each station. Precise time of message receipt and relevant aircraft ID and status information are forwarded to the central processor from each receiver. The central processor then time-clusters the received reports and estimates the position of the aircraft based on the time-difference-of-arrival (TDOA) at the respective ground stations. Since a minimum of three linearly independent time differences are needed to form a three-dimensional position solution (e.g., x,y,z), receptions from at least four stations are required. When more than four receptions are available, a least squares solution (typically maximum likelihood) may be applied so that no information is wasted.
With airborne targets, the worst position error produced by 3D MLAT is generally in the vertical direction. To mitigate such errors in MLAT systems, Mode C altitude measurements reported by the aircraft can be incorporated into the MLAT position solution process. Use of Mode C altitude in MLAT reduces the number of TDOAs required from three to two, thus reducing the number of ground station receptions required from four to three. Use of aircraft reported altitude therefore provides two major benefits in MLAT: improvement of estimate of altitude; and reduction in the number of ground stations required to provide surveillance.
However, errors in reported altitude or “altitude bias” can have a dramatic impact on errors in the horizontal position estimation, and uncorrected altitude errors have the potential to cause severe surveillance problems in multilateration systems. Known solutions of reducing altitude error in multilateration include: accepting the given error conditions and increasing separation standards; employing pressure sensors at the airport and adjusting altitudes similarly to match indicated altitude; avoiding use of altitude data in the multilateration solution; and employing range-aided multilateration. The first option is unacceptable if a robust multilateration system is desired. The second option, use of a surface pressure sensor, can be helpful in some cases, but is a poor solution when unusual altitude/temperature lapse rates are encountered (e.g., temperature inversion). The third option avoids altitude errors, but is prone to much higher jitter, especially in the vertical dimension. Range-aided multilateration has the potential to reduce the jitter problems but suffers from several shortcomings such as: requiring interrogation which can suffer from poor detection in high traffic environments; and specifications for aircraft avionics response time to interrogations are large and result in deficiencies in position accuracy.
Thus, there remains a need for an efficient and more accurate way to correct errors in reported altitude received from aircraft to support multilateration and other potential applications for altitude information.